Climate change is a challenge for insurers in some obvious ways, such as stronger and more frequent natural disasters. Yet there are also more subtle risks to monitor, including changes to insured assets, risks, and exposures. Climate impacts the production quality and quantity of insured consumable goods, their location, and their supply chains. Climate change […]
Climate change is a challenge for insurers in some obvious ways, such as stronger and more frequent natural disasters. Yet there are also more subtle risks to monitor, including changes to insured assets, risks, and exposures. Climate impacts the production quality and quantity of insured consumable goods, their location, and their supply chains.
Climate change can also impact the insurance carrier as an enterprise itself—similarly to cyber risks, insurers underwrite cyber risks for their customers, as well as manage their own risks and exposure as a company. Climate change is similar in the way it will also impact the insurer’s investment portfolio practices.
These kinds of nuanced risk assessments require comprehensive solutions. Evolving your analytics and risk models to accommodate climate change inputs and regulations beyond weather-related natural disasters is increasingly important. Insurers and financial institutions will need to be agile in their approach to include new data sources and update models to enable timely and accurate insights needed to maximize capital efficiency.
Insurance carriers are of course heavily involved in underwriting events related to weather. Natural disasters such as earthquakes, droughts, storms, floods, wildfires, and hurricanes are an unwelcome but expected part of the business. Farming-related insurance is an extension of this. As unpredictable weather patterns continue, these elements must be analyzed at a granular level to manage the risks.
Climate change complicates supply chains, making it difficult to produce the same consistency and quality of raw products. For example, growing rice is very weather dependent. If the impact of climate change is ignored, the critically important, high-quality output of rice grown in India will decrease significantly due to water accessibility. Climate change can have both positive and negative impacts on growing rice—as CO2 rises, the rice yield increases, but the quality of the rice decreases. Constantly monitoring CO2 levels locally and making adjustments accordingly can increase yield. Insurers will have to adjust their models frequently to match local markets.
In addition to production issues, climate impacts distribution, supply chain, and commodity prices of rice. A prominent example was seen in 2008, when a drought in key grain-producing regions—combined with rising biofuel demand, high oil prices, decreasing grain stocks, and the depreciation of the U.S. dollar—led to a spike in global grain prices. That set off a series of rice export bans, furthering shortages and ultimately driving more than 130 million people into poverty and an additional 75 million people into malnourishment. Besides the dramatic impact on global food security, these kinds of events have a massive effect on different insurance lines of businesses. Unfortunately, ongoing climate change might increase the frequency and severity of these types of events.
When deployed smartly, data can help manage the disruption associated with such natural events. Analytics and the increased use of AI can improve underwriting and risk-management practices for customers, insurers, and reinsurers.
The use of climate-related data—such as wind, water, temperature, sun hours, animal and vegetation presence, and historical farm data—frequently processed in real time, can help farmers, food-business workers, and their insurers better predict and manage a changing climate and specific weather events. They can be more proactive about their actions to mitigate such conditions.
For example, farmers are using geolocation information, water and wind sensors, and drones to manage their crops. When this data is aggregated and analyzed in a time series, insurers can improve their underwriting, especially when augmented with historical underwriting and claims data. Constant analysis of the data and creating a loop between data, underwriting decisions, and claims results will enhance the model’s predictive value, improving underwriting and pricing decisions.
This type of data in action is underway in Australia, where advanced AI techniques are helping emergency services better respond. The Australian government is attempting to detect and predict fires earlier using AI sensors. This helps better manage and protect people, homes, and farmlands and is of course helpful to insurers underwriting these properties.
Beyond insurance liability, climate change also poses risks to investment portfolios and the related valuations of insurance carriers.
President Biden announced at the climate summit that the U.S. will target reducing emissions by 50%-52% by 2030 and specified an extensive set of programs to reach this goal as well as support countries around the globe in the initiative. At the same time, the Net-Zero Banking Alliance was also launched. The industry-led alliance brings together 45 banks from 24 countries, which are “committed to aligning their lending and investment portfolios with net-zero emissions by 2050.” This type of initiative further highlights the important role financial services at large have in climate change initiatives.
My colleague Joe Rodriguez’s recent post, “The Intersection of Climate and Capital Markets,” summarized some of the major initiatives underway to address climate change and the economic impacts forthcoming for financial firms, especially related to their investment portfolios. The past 18 months have forced insurers and financial services providers to re-evaluate their business strategies in highly disrupted conditions. Climate change initiatives are also forcing firms to assess their strategies—and while not a new concept, the initiatives are gaining more quantifiable traction. Specific emissions targets and dates, such as those set forth in the U.S., the EU, and other global markets, provide more clarity on the financial impact. An organization’s carbon footprint and readiness to support target standards correspond to tax implications, which in turn affect financial analysis. As it becomes more clear how success is measured and how organizations may be penalized, firms will be better able to assess and proactively manage their own economic risk related to climate change.
Insurers and financial institutions are familiar with the alphabet soup of regulations and the associated modeling requirements—GDPR, IFRS 9, IFRS 17, MiFID 2, NRRA, PBR, PRB, TRIA,CCAR, CECL, CRML, Dodd-Frank, FRTB, and more. This continuous world of regulatory compliance actually helps prepare financial services firms for the implementation of climate-related regulation, since they’re familiar with modeling and a high volume and variety of data. However, modeling for climate change brings a set of unknowns, and firms will require flexibility and agility as they move ahead.
Climate change modeling will challenge organizations to think and act differently. Some of the new variables that insurance companies and financial institutions will need to consider include:
Cloudera Data Platform (CDP) is an enterprise data platform that optimizes risk and exposure management with predictive analytics and machine learning. To learn more about how Cloudera can help financial institutions and insurers manage risk and compliance, read the solution brief.
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